Positron emission tomography (PET) is being used alongside magnetic resonance tomography (MR) in medical diagnostics. While MR is an imaging method for representing structures and slices inside the body, PET allows in vivo visualization and quantification of metabolic activities.
PET uses special properties of positron emitters and positron annihilation in order to quantitatively determine the function of organs and/or cell regions. With this technique, appropriate radiopharmaceuticals marked with radionuclides are administered to the patient prior to the examination. As they decay, the radionuclides emit positrons which after a short distance interact with an electron, causing annihilation to occur. This results in two gamma quanta which fly apart in opposite directions (offset by 180°). The gamma quanta are detected by two opposing PET detector modules within a specific time window (coincidence measurement), as a result of which the annihilation site is localized to a position on the line connecting said two detector modules.
In the case of PET, the detector module generally covers a greater part of a gantry arc length for the purpose of detection. The detector module is subdivided into detector elements having a side length of a few millimeters. On detecting a gamma quantum, each detector element generates an event record that specifies the time and the detection location. This information is passed to a fast logic unit and compared. If two events coincide within a maximum time interval, it is assumed that a gamma decay process is taking place on the connecting line between the two associated detector elements. The PET image is reconstructed using a tomography algorithm, for example, back projection.
In a PET system, such as an MR-PET system, the gamma quanta are attenuated by anything situated between the site of origin of the respective gamma quanta and the PET detector. The attenuation must be taken into account in the reconstruction of PET images in order to prevent image artifacts. Situated between the site of origin of the gamma quantum in the patient's body and the acting PET detector are objects such as tissue within the patient's body, air, and a part of the MR/PET system itself, for example, a patient positioning table. The attenuation values of the objects between the site of origin of the gamma quantum and the acting PET detector are taken into account and compiled into attenuation maps (p maps).
An attenuation map contains attenuation values for each volume element (voxel) of the volume under examination. Thus, for example, an attenuation map can be produced for the patient positioning table. The same applies to, for instance, local coils attached to the patient for MR examinations. In order to produce the attenuation map, the attenuation values are determined and combined. They can be determined by means of, for example, a CT recording or PET transmission measurement of the respective component. Attenuation maps of said kind can be measured on a once-only basis, since the attenuation values do not change over the life of the respective component.
Methods are known by which attenuation values of the patient's body can be determined from anatomical MR images and can be added to the attenuation map. In this case special MR sequences are used by means of which different attenuating tissue classes (e.g., lung tissue), for example, can be identified. With the aid of the MR images it is then possible, based on the position of the attenuating tissue class, to assign appropriate attenuation values to the attenuation map.
However, a transaxial MR field of view is generally smaller than the PET field of view. Therefore, a portion of an object to be examined is only in the PET field of view. Consequently, obtaining attenuation values outside the MR field of view becomes difficult.
MR based estimation of a PET attenuation map may be done either by segmenting the MR image into different tissue types and assigning corresponding attenuation values to the different tissue types. However, this approach does not address the scanned areas outside of the MR field of view.
Recently, maximum-likelihood expectation maximization (MLEM algorithms) has been used to simultaneously reconstruct emission and attenuation maps from PET sinogram data. The PET sinogram data may be referred to as PET raw data, PET counts or PET count data. The term “image” is an image reconstructed from the PET sinogram data. An attenuation map from an MR based segmentation or another known method can be used to initialize the MLEM algorithm.
Other approaches for MR based attenuation correction include the use of an atlas, model or reference image with a known attenuation such as a coregistered corresponding CT, PET transmission image or body contours derived from optical 3D scanning. The actual MR image is then registered to the atlas or reference with known attenuation and the actual attenuation map is deduced from the registration information and additional post-processing methods.